Run the ELK (Elasticseach, Logstash, Kibana) stack with Docker and Docker-compose.
NOTE: This stack runs Elasticseach 1.7.x, Logstash 1.5.x and the latest version of Kibana 4.
It will give you the ability to quickly test your logstash filters and check how the data can be processed in Kibana.
Based on the official images:
- Install Docker.
- Install Docker-compose.
- Clone this repository
On distributions which have SELinux enabled out-of-the-box you will need to either re-context the files or set SELinux into Permissive mode in order for fig-elk to start properly. For example on Redhat and CentOS, the following will apply the proper context:
.-root@centos ~
-$ chcon -R system_u:object_r:admin_home_t:s0 fig-elk/Start the ELK stack using docker-compose:
$ docker-compose upYou can also choose to run it in background (detached mode):
$ docker-compose up -dNow that the stack is running, you'll want to inject logs in it. The shipped logstash configuration allows you to send content via tcp:
$ nc localhost 5000 < /path/to/logfile.logAnd then access Kibana UI by hitting http://localhost:5601 with a web browser.
By default, the stack exposes the following ports:
- 5000: Logstash TCP input.
- 9200: Elasticsearch HTTP (with Marvel plugin accessible via http://localhost:9200/_plugin/marvel)
- 5601: Kibana 4 web interface
WARNING: If you're using boot2docker, you must access it via the boot2docker IP address instead of localhost.
WARNING: If you're using Docker Toolbox, you must access it via the docker-machine IP address instead of localhost.
NOTE: Configuration is not dynamically reloaded, you will need to restart the stack after any change in the configuration of a component.
The Kibana default configuration is stored in kibana/config/kibana.yml.
The logstash configuration is stored in logstash/config/logstash.conf.
The folder logstash/config is mapped onto the container /etc/logstash/conf.d so you
can create more than one file in that folder if you'd like to. However, you must be aware that config files will be read from the directory in alphabetical order.
The Logstash container use the LS_HEAP_SIZE environment variable to determine how much memory should be associated to the JVM heap memory (defaults to 500m).
If you want to override the default configuration, add the LS_HEAP_SIZE environment variable to the container in the docker-compose.yml:
logstash:
image: logstash:latest
command: logstash -f /etc/logstash/conf.d/logstash.conf
volumes:
- ./logstash/config:/etc/logstash/conf.d
ports:
- "5000:5000"
links:
- elasticsearch
environment:
- LS_HEAP_SIZE=2048mAs for the Java heap memory, another environment variable allows to specify JAVA_OPTS used by Logstash. You'll need to specify the appropriate options to enable JMX and map the JMX port on the docker host.
Update the container in the docker-compose.yml to add the LS_JAVA_OPTS environment variable with the following content (I've mapped the JMX service on the port 18080, you can change that), do not forget to update the -Djava.rmi.server.hostname option with the IP address of your Docker host (replace DOCKER_HOST_IP):
logstash:
image: logstash:latest
command: logstash -f /etc/logstash/conf.d/logstash.conf
volumes:
- ./logstash/config:/etc/logstash/conf.d
ports:
- "5000:5000"
- "18080:18080"
links:
- elasticsearch
environment:
- LS_JAVA_OPTS=-Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.ssl=false -Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun.management.jmxremote.port=18080 -Dcom.sun.management.jmxremote.rmi.port=18080 -Djava.rmi.server.hostname=DOCKER_HOST_IP -Dcom.sun.management.jmxremo
63A5
te.local.>The Elasticsearch container is using the shipped configuration and it is not exposed by default.
If you want to override the default configuration, create a file elasticsearch/config/elasticsearch.yml and add your configuration in it.
Then, you'll need to map your configuration file inside the container in the docker-compose.yml. Update the elasticsearch container declaration to:
elasticsearch:
build: elasticsearch/
ports:
- "9200:9200"
volumes:
- ./elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.ymlIn order to persist Elasticsearch data, you'll have to mount a volume on your Docker host. Update the elasticsearch container declaration to:
elasticsearch:
build: elasticsearch/
ports:
- "9200:9200"
volumes:
- /path/to/storage:/usr/share/elasticsearch/dataThis will store elasticsearch data inside /path/to/storage.